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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Gutiérrez, Rafael
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (16/16 displayed)
- 2024Computational Design of the Electronic Response for Volatile Organic Compounds Interacting with Doped Graphene Substrates
- 2022Magnetoresistive Single-Molecule Junctionscitations
- 2021Predicting Neuropsychological Impairment in Relapsing Remitting Multiple Sclerosis: The Role of Clinical Measures, Treatment, and Neuropsychiatry Symptomscitations
- 2020Interactions of Long-Chain Polyamines with Silica Studied by Molecular Dynamics Simulations and Solid-State NMR Spectroscopycitations
- 2020Towards synthetic neural networkscitations
- 2019Quantum Phonon Transport in Nanomaterials: Combining Atomistic with Non-Equilibrium Green’s Function Techniquescitations
- 2019Direct Assembly and Metal-Ion Binding Properties of Oxytocin Monolayer on Gold Surfacescitations
- 2019Doping engineering of thermoelectric transport in BNC heteronanotubescitations
- 2019Thermal bridging of graphene nanosheets via covalent molecular junctionscitations
- 2018Chirality-dependent electron spin filtering by molecular monolayers of helicenescitations
- 2017In-Situ Stretching Patterned Graphene Nanoribbons in the Transmission Electron Microscopecitations
- 2015Switchable Negative Differential Resistance Induced by Quantum Interference Effects in Porphyrin-based Molecular Junctionscitations
- 2010Structural stability versus conformational sampling in biomolecular systems: Why is the charge transfer efficiency in G4-DNA better than in double-stranded DNA?citations
- 2009Combined density functional theory and Landauer approach for hole transfer in DNA along classical molecular dynamics trajectoriescitations
- 2007Tuning the conductance of a molecular switchcitations
- 2003Conductance of a molecular junction mediated by unconventional metal-induced gap statescitations
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article
Predicting Neuropsychological Impairment in Relapsing Remitting Multiple Sclerosis: The Role of Clinical Measures, Treatment, and Neuropsychiatry Symptoms
Abstract
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>This retrospective observational study aimed to define neuropsychological impairment (NI) profiles and determine the influence of clinical, demographic, and neuropsychiatric measures in specific cognitive domains in a cohort of relapsing–remitting multiple sclerosis (RRMS) patients.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Ninety-one RRMS patients underwent a neurological examination and a brief neuropsychological assessment. Patients were classified according to the disease-modifying therapies (DMTs) received (platform or high-efficacy). Differences between groups and multiple regression analyses were performed to determine the predictive value of the assessed measures in cognitive performance.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>More than two-thirds of the patients showed NI. Specifically, mild to moderate NI was presented in approximately half of the participants. Paced Auditory Serial Addition Test (PASAT-3) and Symbol Digit Modalities Test (SDMT) were the most frequently impaired cognitive tests (45.3% and 41.3%, respectively) followed by phonemic verbal fluency (PVF) (27.8%). Expanded Disability Status Scale (EDSS), age, depressive symptoms, and disease duration were the best predictors of SDMT (R2 = .34; p &lt; .01), whereas disease duration, EDSS, and anxiety-state levels predicted PASAT-3 (R2 = .33, p &lt; .01). Educational level, age, EDSS, and depressive symptoms demonstrated the strongest association with PVF (R2 = .31, p &lt; .01).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our results indicated a significant prevalence of NI in RRMS patients that was not dependent on the DMT type. In addition to the meaningful working memory (PASAT-3) and information processing speed (SDMT) impairments found, PVF deficits may also be an important marker of cognitive impairment in RRMS patients. This study supports the relevance of standard clinical measures and reinforces the importance of quantifying clinical and neuropsychiatric symptoms to predict subsequent cognitive performance on a similar multiple sclerosis phenotype and disease stage.</jats:p></jats:sec>